Merge Raster data
setwd("D:/mpg/daten/areal/aerial_croped")
library(sp)
library(raster)
library(rgdal)
library(glcm)
all <- merge(r1, r2, r3, r4, r5, r6)
projection(all) <- CRS("+init=epsg:25832")
writeRaster(all, "merge_caldern", format = "GTiff")
library(sp)
library(raster)
library(rgdal)
## rgdal: version: 1.2-15, (SVN revision 691)
## Geospatial Data Abstraction Library extensions to R successfully loaded
## Loaded GDAL runtime: GDAL 2.2.0, released 2017/04/28
## Path to GDAL shared files: C:/Users/Collin Weber/Documents/R/win-library/3.4/rgdal/gdal
## GDAL binary built with GEOS: TRUE
## Loaded PROJ.4 runtime: Rel. 4.9.3, 15 August 2016, [PJ_VERSION: 493]
## Path to PROJ.4 shared files: C:/Users/Collin Weber/Documents/R/win-library/3.4/rgdal/proj
## Linking to sp version: 1.2-5
library(glcm)
caldern <- raster("D:/mpg/daten/areal/aerial_croped/merge_caldern.tif")
plot(caldern, main = "Merge all raster")
Create one band rasters
merge <- stack("merge_caldern.tif")
merge_blue <- merge[[3]]
merge_green <- merge[[2]]
merge_red <- merge[[1]]
writeRaster(merge_blue, "merge_cal_blue", format = "GTiff")
writeRaster(merge_green, "merge_cal_green", format = "GTiff")
writeRaster(merge_red, "merge_cal_red", format = "GTiff")
blue <- raster("D:/mpg/daten/areal/aerial_croped/merge_cal_blue.tif")
green <- raster("D:/mpg/daten/areal/aerial_croped/merge_cal_green.tif")
red <- raster("D:/mpg/daten/areal/aerial_croped/merge_cal_red.tif")
plot(blue, main = "blue-band")
plot(green, main = "green-band")
plot(red, main = "red-band")
NGRDI Index
green <- brick("merge_cal_green.tif")
red <- brick("merge_cal_red.tif")
NGRDI <- (green-red)/(green+red)
writeRaster(NGRDI, "NGRDI_gesamt_caldern", format = "GTiff")
ngr <- raster("D:/mpg/daten/areal/aerial_croped/NGRDI_gesamt_caldern.tif")
plot(ngr, col= terrain.colors(30), main = "NGRDI-Index")
NGRDI Index with “mean” and “variation” spatial filter (cell size: 9x9)
NGRDI_cal_mean_9x9 <- glcm(ng, window = c(9, 9), statistics = "mean")
writeRaster(NGRDI_cal_mean_9x9, "NGRDI_mean_9x9_caldern", format = "GTiff")
NGRDI_cal_variance_9x9 <- glcm(ng, window = c(9, 9), statistics = "variance")
writeRaster(NGRDI_cal_variance_9x9, "NGRDI_variance_9x9_caldern", format = "GTiff")
mean <- raster("D:/mpg/daten/areal/aerial_croped/NGRDI_mean_9x9_caldern.tif")
var <- raster("D:/mpg/daten/areal/aerial_croped/NGRDI_variance_9x9_caldern.tif")
plot(mean, col= terrain.colors(30), main = "NGRDI Filter: mean (9x9)")
plot(var, col= terrain.colors(30), main = "NGRDI Filter: variance (9x9)")
